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Dominant Color Extraction with K-Means for Camera Characterization in Cultural Heritage Documentation
Article

From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage

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Department of Architecture, Built Environment, and Construction Engineering, Politecnico di Milano. 31 Giuseppe Ponzio Street, 20133 Milan, Italy
2
Departamento de Expresión Gráfica e Ingeniería en la Edificación, Escuela Técnica Superior de Ingeniería de Edificación, Universidad de Sevilla. 4A Reina Mercedes Avenue, 41012 Seville, Spain
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Departamento de Prehistoria y Arqueología, Facultad de Geografía e Historia, Universidad de Sevilla. Doña María de Padilla Street, 41004 Seville, Spain
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The Creative and Virtual Technologies Research Laboratory, School of Architecture, Design and the Built Environment, Nottingham Trent University, 50 Shakespeare Street, Nottingham NG1 4FQ, UK
*
Author to whom correspondence should be addressed.
Received: 4 March 2020 / Revised: 21 March 2020 / Accepted: 25 March 2020 / Published: 29 March 2020
Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information Modelling (HBIM) approach is able to cover the comprehensive restoration of the building. In contrast to BIM applied to new buildings, HBIM can address different models which represent either periods of historical interpretation, restoration phases or records of heritage assets over time. Great efforts are currently being made to automatically reconstitute the geometry of cultural heritage elements from data acquisition techniques such as Terrestrial Laser Scanning (TLS) or Structure From Motion (SfM) into BIM (Scan-to-BIM). Hence, this work advances on the parametric modelling from remote sensing point cloud data, which is carried out under the Rhino+Grasshopper-ArchiCAD combination. This workflow enables the automatic conversion of TLS and SFM point cloud data into textured 3D meshes and thus BIM objects to be included in the HBIM project. The accuracy assessment of this workflow yields a standard deviation value of 68.28 pixels, which is lower than other author’s precision but suffices for the automatic HBIM of the case study in this research. View Full-Text
Keywords: parametric modelling; Scan-to-BIM; cultural heritage; point cloud data parametric modelling; Scan-to-BIM; cultural heritage; point cloud data
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MDPI and ACS Style

Andriasyan, M.; Moyano, J.; Nieto-Julián, J.E.; Antón, D. From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage. Remote Sens. 2020, 12, 1094. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071094

AMA Style

Andriasyan M, Moyano J, Nieto-Julián JE, Antón D. From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage. Remote Sensing. 2020; 12(7):1094. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071094

Chicago/Turabian Style

Andriasyan, Mesrop, Juan Moyano, Juan E. Nieto-Julián, and Daniel Antón. 2020. "From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage" Remote Sensing 12, no. 7: 1094. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071094

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